AIMC Topic: Single-Cell Gene Expression Analysis

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Methods for cell-type annotation on scRNA-seq data: A recent overview.

Journal of bioinformatics and computational biology Sep 23, 2023
The evolution of single-cell technology is ongoing, continually generating massive amounts of data that reveal many mysteries surrounding intricate diseases. However, their drawbacks continue to constrain us. Among these, annotating cell types in sin...
Neural Networks, Computer Gene Expression Profiling Single-Cell Gene Expression Analysis Sequence Analysis, RNA
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scTIGER: A Deep-Learning Method for Inferring Gene Regulatory Networks from Case versus Control scRNA-seq Datasets.

International journal of molecular sciences Aug 28, 2023
Inferring gene regulatory networks (GRNs) from single-cell RNA-seq (scRNA-seq) data is an important computational question to find regulatory mechanisms involved in fundamental cellular processes. Although many computational methods have been designe...
Humans Mitogen-Activated Protein Kinases Gene Regulatory Networks Fear Single-Cell Gene Expression Analysis Male Prostatic Neoplasms Deep Learning
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Transfer learning enables predictions in network biology.

Nature May 31, 2023
Mapping gene networks requires large amounts of transcriptomic data to learn the connections between genes, which impedes discoveries in settings with limited data, including rare diseases and diseases affecting clinically inaccessible tissues. Recen...
Single-Cell Gene Expression Analysis Biology Datasets as Topic Cardiomyopathies Humans Chromatin Neural Networks, Computer Machine Learning
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Single-cell RNA-seq data analysis based on directed graph neural network.

Methods (San Diego, Calif.) Feb 16, 2023
Single-cell RNA sequencing (scRNA-seq) data scale surges with high-throughput sequencing technology development. However, although single-cell data analysis is a powerful tool, various issues have been reported, such as sequencing sparsity and comple...
Cluster Analysis High-Throughput Nucleotide Sequencing Single-Cell Analysis Single-Cell Gene Expression Analysis Sequence Analysis, RNA Neural Networks, Computer Data Analysis Gene Expression Profiling
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Cross-species cell-type assignment from single-cell RNA-seq data by a heterogeneous graph neural network.

Genome research Dec 16, 2022
Cross-species comparative analyses of single-cell RNA sequencing (scRNA-seq) data allow us to explore, at single-cell resolution, the origins of the cellular diversity and evolutionary mechanisms that shape cellular form and function. Cell-type assig...
Mice Sequence Analysis, RNA Genome Gene Regulatory Networks Single-Cell Gene Expression Analysis Humans Neural Networks, Computer Animals Biomarkers Gene Expression Profiling Single-Cell Analysis
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Protocol for fast scRNA-seq raw data processing using scKB and non-arbitrary quality control with COPILOT.

STAR protocols Sep 30, 2022
We describe a protocol to perform fast and non-arbitrary quality control of single-cell RNA sequencing (scRNA-seq) raw data using scKB and COPILOT. scKB is a wrapper script of kallisto and bustools for accelerated alignment and transcript count matri...
Software Single-Cell Analysis Single-Cell Gene Expression Analysis Sequence Analysis, RNA Quality Control
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Differentiable graph clustering with structural grouping for single-cell RNA-seq data.

Bioinformatics (Oxford, England) Jul 1, 2025
MOTIVATION: Clustering cells into subpopulations is one of the most crucial tasks in single-cell RNA sequencing (scRNA-seq) data analysis, which provides support for biological research at cellular level. With the development of graph neural networks...
Humans Neural Networks, Computer Algorithms Single-Cell Analysis RNA-Seq Computational Biology Single-Cell Gene Expression Analysis Sequence Analysis, RNA Cluster Analysis
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Identification of potential biomarkers in cardiovascular calcification based on bioinformatics combined with single-cell RNA-seq and multiple machine learning analysis.

Cellular signalling Jul 1, 2025
BACKGROUND: The molecular and genetic mechanisms underlying vascular calcification remain unclear. This study aimed to determine the differences in calcification marker-related gene expression in macrophages.
Protein Interaction Maps RNA-Seq Single-Cell Gene Expression Analysis Mice Computational Biology Vascular Calcification Biomarkers Animals Single-Cell Analysis Humans Machine Learning
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Integrating bulk RNA-seq and scRNA-seq analyses with machine learning to predict platinum response and prognosis in ovarian cancer.

Scientific reports May 31, 2025
Platinum-based therapy is an integral part of the standard treatment for ovarian cancer. However, despite extensive research spanning several decades, the identification of dependable predictive biomarkers for platinum response in clinical practice h...
Humans Ovarian Neoplasms Gene Expression Profiling RNA-Seq Platinum Machine Learning Transcriptome Female Single-Cell Gene Expression Analysis Prognosis Drug Resistance, Neoplasm Biomarkers, Tumor Single-Cell Analysis Gene Expression Regulation, Neoplastic Antineoplastic Agents
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Identification of novel therapeutic targets in hepatitis-B virus-associated membranous nephropathy using scRNA-seq and machine learning.

Scientific reports May 29, 2025
Hepatitis B Virus-associated membranous nephropathy (HBV-MN) significantly impacts renal health, particularly in areas with high HBV prevalence. Understanding the molecular mechanisms underlying HBV-MN is crucial for developing effective therapeutic ...
Hepatitis B virus Hepatitis B Single-Cell Analysis Humans Machine Learning Glomerulonephritis, Membranous Podocytes RNA-Seq Single-Cell Gene Expression Analysis MicroRNAs
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